-averse decision-maker. Modelling an expected utility maximizing decision maker, the problem is formulated as a risk-sensitive Markov … decision process. Special emphasis is put on the existence of structured optimal policies. Numerical examples illustrate the …Traditionally, revenue management models aim at a maximization of expected revenue, i.e. a risk-neutral decision …

in the literature, and then shows in detail how this problem can be modeled as a Markov decision process and presents …

This book presents classical Markov Decision Processes (MDP) for real-life applications and optimization. MDP allows … users to develop and formally support approximate and simple decision rules, and this book showcases state … Policies In Mdps With Unbounded Jumps: The State Of Our Art -- Markov Decision Processes For Screening And Treatment Of Chronic …

problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First … combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision …-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book’s final chapter is …